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  • Open Access

    ARTICLE

    Smart Contract Fuzzing Based on Taint Analysis and Genetic Algorithms

    Zaoyu Wei1,*, Jiaqi Wang2, Xueqi Shen1, Qun Luo1

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 35-45, 2020, DOI:10.32604/jihpp.2020.010331

    Abstract Smart contract has greatly improved the services and capabilities of blockchain, but it has become the weakest link of blockchain security because of its code nature. Therefore, efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system. Oriented to Ethereum smart contract, the study solves the problems of redundant input and low coverage in the smart contract fuzz. In this paper, a taint analysis method based on EVM is proposed to reduce the invalid input, a dangerous operation database is designed to identify the dangerous input, and genetic algorithm is used to optimize the… More >

  • Open Access

    ARTICLE

    Developing an Adaptation Process for Real-Coded Genetic Algorithms

    Ridvan Saraçoğlu*, Ahmet Fatih Kazankaya

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

    Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a shorter time. Experimental results show… More >

  • Open Access

    ARTICLE

    A Clustering-based Approach for Balancing and Scheduling Bicycle-sharing Systems

    Imed Kacem, Ahmed Kadri, Pierre Laroche

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 421-430, 2018, DOI:10.31209/2018.100000016

    Abstract This paper addresses an inventory regulation problem in bicycle sharingsystems. The problem is to balance a network consisting of a set of stations by using a single vehicle, with the aim of minimizing the weighted sum of the waiting times during which some stations remain imbalanced. Motivated by the complexity of this problem, we propose a two-stage procedure based on decomposition. First, the network is divided into multiple zones by using two different clustering strategies. Then, the balancing problem is solved in each zone. Finally, the order in which the zones must be visited is defined. To solve these problems,… More >

  • Open Access

    ARTICLE

    A Genetic Algorithm to Solve Capacity Assignment Problem in a Flow Network

    Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1579-1586, 2020, DOI:10.32604/cmc.2020.010881

    Abstract Computer networks and power transmission networks are treated as capacitated flow networks. A capacitated flow network may partially fail due to maintenance. Therefore, the capacity of each edge should be optimally assigned to face critical situations—i.e., to keep the network functioning normally in the case of failure at one or more edges. The robust design problem (RDP) in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure. The RDP is known as NP-hard. Thus, capacity assignment problem subject to system reliability and total… More >

  • Open Access

    ARTICLE

    Smart Contract Fuzzing Based on Taint Analysis and Genetic Algorithms

    Zaoyu Wei1, *, Jiaqi Wang2, Xueqi Shen1, Qun Luo1

    Journal of Quantum Computing, Vol.2, No.1, pp. 11-24, 2020, DOI:10.32604/jqc.2020.010815

    Abstract Smart contract has greatly improved the services and capabilities of blockchain, but it has become the weakest link of blockchain security because of its code nature. Therefore, efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system. Oriented to Ethereum smart contract, the study solves the problems of redundant input and low coverage in the smart contract fuzz. In this paper, a taint analysis method based on EVM is proposed to reduce the invalid input, a dangerous operation database is designed to identify the dangerous input, and genetic algorithm is used to optimize the… More >

  • Open Access

    ABSTRACT

    Numerical prediction and sequential process optimization in sheet forming based on genetic algorithm

    Schmidt1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.15, No.2, pp. 65-74, 2010, DOI:10.3970/icces.2010.015.065

    Abstract Genetic algorithm is an emerging technique used in engineering design activities to find an optimized solution which satisfy a number of design goals. Non-linear direct method of goal search use successive linearization techniques, which are sensitive to the chosen starting solution and quality of the objective function. The proposed technique can solve programming problems having non-convex regions, which are usually avoided in classical optimization problems. The efficacy of the proposed novel method is demonstrated by solving a number of test problems. The results suggest that the proposed method is effective and represents a practical tool for solving sheet forming problems. More >

  • Open Access

    ABSTRACT

    Using genetic algorithms to find a globally optimal solution in uncertain environments with multiple sources of additive and multiplicative noise

    Takéhiko Nakama1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.4, pp. 233-242, 2009, DOI:10.3970/icces.2009.009.233

    Abstract Random noise perturbs objective functions in a variety of practical optimization problems, and genetic algorithms (GAs) have been widely proposed as an effective optimization tool for dealing with noisy objective functions. In this paper, we investigate GAs applied to objective functions that are perturbed by multiple sources of additive and multiplicative noise that each take on finitely many values. We reveal the convergence properties of GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms in noisy environments. Our analysis shows that this Markov chain is indecomposable; it has only one positive recurrent communication… More >

  • Open Access

    ARTICLE

    Construction of Integral Objective Function/Fitness Function of Multi-Objective/Multi-Disciplinary Optimization

    Z. Q. Zhu1, Z. Liu1, X. L. Wang1, R. X. Yu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.6, No.6, pp. 567-576, 2004, DOI:10.3970/cmes.2004.006.567

    Abstract To extend an available mono-objective optimization method to multi-objective/multi-disciplinary optimization, the construction of a suitable integral objective function (in gradient based deterministic method-DM) or fitness function (in genetic algorithm-GA) is important. An auto-adjusting weighted object optimization (AWO) method in DM is suggested to improve the available weighted sum method (linear combined weighted object optimizationLWO method). Two formulae of fitness function in GA are suggested for two kinds of design problems. Flow field solution is obtained by solving Euler equations. Electromagnetic field solution is obtained by solving Maxwell equations. Bi-disciplinary optimization computation is carried out by coupling these two solutions with… More >

  • Open Access

    ARTICLE

    Generating optimised partitions for parallel finite element computations employing float-encoded genetic algorithms

    A. Rama Mohan Rao1, T.V.S.R. Appa Rao2, B. Dattaguru3

    CMES-Computer Modeling in Engineering & Sciences, Vol.5, No.3, pp. 213-234, 2004, DOI:10.3970/cmes.2004.005.213

    Abstract This paper presents an algorithm for automatic partitioning of unstructured meshes for parallel finite element computations employing float-encoded genetic algorithms (FEGA). The problem of mesh partitioning is represented in such a way that the number of variables considered in the genome (chromosome) construction is constant irrespective of the size of the problem. In order to accelerate the computational process, several acceleration techniques like constraining the search space, local improvement after initial global partitioning have been attempted. Finally, micro float-encoded genetic algorithms have been developed to accelerate the computational process. More >

  • Open Access

    ARTICLE

    Radial Basis Function and Genetic Algorithms for Parameter Identification to Some Groundwater Flow Problems

    B. Amaziane1, A. Naji2, D. Ouazar3

    CMC-Computers, Materials & Continua, Vol.1, No.2, pp. 117-128, 2004, DOI:10.3970/cmc.2004.001.117

    Abstract In this paper, a meshless method based on Radial Basis Functions (RBF) is coupled with genetic algorithms for parameter identification to some selected groundwater flow applications. The treated examples are generated by the diffusion equation with some specific boundary conditions describing the groundwater fluctuation in a leaky confined aquifer system near open tidal water. To select the best radial function interpolation and show the powerful of the method in comparison to domain based discretization methods, Multiquadric (MQ), Thin-Plate Spline (TPS) and Conical type functions are investigated and compared to finite difference results or analytical one. Through two sample problems in… More >

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